{"id":"W2097308479","doi":"10.1002/meet.2009.1450460119","title":"Media Informatics: Theory, methods, and tools","year":2009,"lang":"en","type":"article","venue":"Proceedings of the American Society for Information Science and Technology","topic":"Multimedia Communication and Technology","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Informatics; Social media; Digital media; Engineering informatics; Data science; New media; Multimedia; World Wide Web; Health informatics; Engineering; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.003753425,0.0000772989,0.0001815899,0.0002474718,0.0007937994,0.0001451267,0.0008782183,0.00008837491,0.00000158687],"category_scores_gemma":[0.00475649,0.00005769327,0.00005438872,0.002229234,0.0072651,0.002244191,0.0002181533,0.0001488462,8.741176e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004958257,"about_ca_system_score_gemma":0.0001600721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001527018,"about_ca_topic_score_gemma":0.000001775133,"domain_scores_codex":[0.9990349,0.000006738327,0.0003045457,0.0000824532,0.0002965403,0.0002747717],"domain_scores_gemma":[0.9981149,0.0002533829,0.0005572684,0.000141689,0.0008741247,0.00005860844],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.000003056231,0.000003927036,0.0001831475,0.000005357607,0.000003649638,4.185112e-10,0.009369093,1.957042e-8,0.001170359,0.5427266,0.0002000726,0.4463347],"study_design_scores_gemma":[0.0005704237,0.0002150537,0.004704189,0.00003297133,0.00004124444,0.000008006761,0.3939081,0.001131131,0.01548252,0.248808,0.3348165,0.0002819071],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8819996,0.0001842174,0.003554996,0.06829895,0.0001445715,0.001452784,0.00001701676,0.0005429108,0.04380492],"genre_scores_gemma":[0.8715359,0.0006165363,0.1260068,0.001781638,0.00001063631,0.00003105104,6.356381e-7,0.000002014978,0.00001475207],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4460528,"threshold_uncertainty_score":0.9954365,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02473636007719308,"score_gpt":0.3596529095956585,"score_spread":0.3349165495184654,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}